train.py

import pickle
from sklearn.datasets import make_classification
from sklearn.linear_model import LogisticRegression

x, y = make_classification(n_samples=100, 
                           n_features=3, 
                           n_informative=2, 
                           n_classes=2, 
                           n_redundant=0, 
                           n_repeated=0,)

lr = LogisticRegression()
lr.fit(x,y)

with open('model.pickle', 'wb') as f:
    pickle.dump(lr, f)